Octopus Format Analysis

McCade Pearson

2025-06-17

legs <- sort(c(rep(seq(1, 7), 10), rep(8, 12)))
getPoints <- function(wins) {
  case_when(wins == 0 ~ 0,
            wins == 1 ~ 1,
            wins == 2 ~ 1,
            wins == 3 ~ 2, 
            wins == 4 ~ 2, 
            wins == 5 ~ 3, 
            wins == 6 ~ 3, 
            wins == 7 ~ 4, 
            wins == 8 ~ 4, 
            wins == 9 ~ 5, 
            wins == 10 ~ 5, 
            wins == 11 ~ 6, 
            wins == 12 ~ 6)}
getPoints2 <- function(wins) {
  case_when(wins == 0 ~ 0,
            wins == 1 ~ 1,
            wins == 2 ~ 2,
            wins == 3 ~ 4, 
            wins == 4 ~ 6, 
            wins == 5 ~ 9, 
            wins == 6 ~ 12, 
            wins == 7 ~ 16, 
            wins == 8 ~ 20, 
            wins == 9 ~ 25, 
            wins == 10 ~ 30, 
            wins == 11 ~ 36, 
            wins == 12 ~ 42)}
all_schedule <- hoopR::load_nba_schedule()
all_schedule <- all_schedule %>%
  mutate(date = lubridate::ymd_hm(date)-28800) %>%
  filter(type_abbreviation == "STD") %>%
  filter(season_type == 2) %>%
  filter(status_type_id == 3)
east <- c("MIL", "BOS", "PHI", "CLE", "BKN", "NY", "MIA", "DET", "ATL", "TOR", "WSH", "IND", "CHI", "ORL", "CHA")
Teams <- all_schedule %>%
  select(home_name, home_color, home_logo, home_color, home_alternate_color, home_display_name, home_abbreviation) %>%
  distinct()

get_schedule <- function(TeamName) {
  HomeGames <- all_schedule %>%
  filter(home_name == TeamName) %>%
  select(date, home_name, home_score, away_name, away_abbreviation, away_logo, away_score, away_color, away_alternate_color, game_id) %>%
  mutate(Team = home_name,
         TeamScore = home_score,
         OpponentScore = away_score,
         Opponent = away_name,
         Opponent2 = away_abbreviation,
         OpponentLogo = away_logo) %>%
  mutate(TeamWin = ifelse(home_score > away_score, 1, 0),
         Game = "Home") %>%
  select(date, Team, TeamScore, OpponentScore, Opponent, Opponent2, OpponentLogo,TeamWin, Game, game_id)
AwayGames <- all_schedule %>%
  filter(away_name == TeamName) %>%
  select(date, away_name, away_score, home_name, home_abbreviation, home_logo, home_score, home_color, home_alternate_color, game_id) %>%
  mutate(Team = away_name,
         TeamScore = away_score,
         OpponentScore = home_score,
         Opponent = home_name,
         Opponent2 = home_abbreviation,
         OpponentLogo = home_logo) %>%
  mutate(TeamWin = ifelse(away_score > home_score, 1, 0),
         Game = "Away") %>%
  select(date, Team, TeamScore, OpponentScore, Opponent, Opponent2, OpponentLogo, TeamWin, Game, game_id)
Games <- rbind(HomeGames, AwayGames)
Games <- Games %>%
  arrange((date)) %>%
  mutate(Leg = legs) %>%
  group_by(Leg) %>%
  mutate(RunWins = cumsum(TeamWin),
         Points = ifelse(TeamWin == 1, getPoints(RunWins), 0),
         PointsPlaying = ifelse(TeamWin == 1, getPoints(RunWins), getPoints(RunWins+1)),
         GameLeg = 1:n()) %>%
  ungroup() %>%
  mutate(RunningPts = cumsum(Points))
return(Games)}
Schedules <- list()
for (team in Teams$home_name) {
  Schedules[[team]] <- get_schedule(team)}

Standings <- data.frame()
for(team_name in Teams$home_name) {
Standings2 <- Schedules[[team_name]] %>%
  ungroup() %>%
  group_by(Leg) %>%
  mutate(AllWins = ifelse(date >= Today, 1, TeamWin),
         RunWins = cumsum(TeamWin),
         Points = ifelse(TeamWin == 1, getPoints(RunWins), 0),
         MaxRunWins = cumsum(AllWins),
         MaxPoints = ifelse(AllWins == 1, getPoints(MaxRunWins), 0),
         PointsPlayedFor = ifelse(TeamScore > 0, getPoints(RunWins+1), 0)) %>%
  ungroup() %>%
  group_by(Team) %>%
  summarise(GP = sum(TeamScore > 0),
            W = sum(TeamWin),
            L = GP-W,
            Pts = sum(Points),
            MPts = sum(MaxPoints),
            PtsPlayed = sum(PointsPlayedFor),
            PtsLost = PtsPlayed-Pts,
            AdjWP = Pts/PtsPlayed,
            WP = W/GP,
            PPG = Pts/GP,
            PPW = Pts/W,
            PD = (sum(TeamScore)/GP)-(sum(OpponentScore)/GP),
            WL = paste0(W,"-",L),
            AdjWL = paste0(Pts,"-",PtsLost),
            PD = round(PD,2),
            PtsPlayed = PtsPlayed/GP,
            PD = ifelse(PD >= 0, paste0("+",PD), PD)) %>%
  left_join(Teams, by = c('Team' = 'home_name')) %>%
  select(home_logo, home_abbreviation, Pts, WL, WP, AdjWL, AdjWP, PPG, PPW, MPts, PD, Team)
  Standings <- rbind(Standings, Standings2)}


EastStandings <- Standings %>%
  filter(home_abbreviation %in% east) %>%
  select(-home_abbreviation) %>%
  arrange(-Pts, PPW, -AdjWP) %>%
  mutate(Rk = 1:15) %>%
  select(12, 1:11)
gt(EastStandings) %>%
  gt_theme_espn() %>%
  cols_align(columns = everything(), align = c('center')) %>%
  cols_align(columns = c(Rk), align = c('right')) %>%
  text_transform(
    locations = cells_body(columns = home_logo),
    fn = function(x) {
      web_image(url = EastStandings$home_logo, height = as.numeric(40))}) %>%
  fmt_percent(columns = c(WP, AdjWP), decimals = 2) %>%
  fmt_number(columns = c(PPG, PPW)) %>%
  gt_highlight_rows(rows = 1:6, fill = "#8CD47E") %>%
  gt_highlight_rows(rows = 7:10, fill = "#F8D66D") %>%
  gt_highlight_rows(rows = 11:15, fill = "#FF6961") %>%
  tab_style(style = list(cell_fill(color = "black"), cell_text(color = "white", align = "center")), locations = cells_column_labels()) %>%
  cols_label(home_logo = "", 
             WL = "W-L",
             WP = "Pct",
             AdjWL = "Adj. W-L",
             AdjWP = "Adj. Pct",
             MPts = "Max Pts") %>%
  cols_width(Rk ~ px(25), home_logo ~ px(67), Pts ~ px(50), WL ~ px(60), WP ~ px(60), AdjWL ~ px(75), AdjWP ~ px(75), PPG ~ px(50), PPW ~ px(50), MPts ~ px(75), PD ~ px(60)) %>%
  tab_header(title = "EASTERN CONFERENCE STANDINGS") %>%
  tab_style(style = list(cell_fill(color = "#17408B"), cell_text(color = "white", align = "center")), locations = cells_title()) %>%
  cols_hide(Team)

EASTERN CONFERENCE STANDINGS
Rk		Pts	W-L	Pct	Adj. W-L	Adj. Pct	PPG	PPW	Max Pts	PD
1		165	64-18	78.05%	165-95	63.46%	2.01	2.58	165	+9.54
2		151	61-21	74.39%	151-92	62.14%	1.84	2.48	151	+9.11
3		111	51-31	62.20%	111-93	54.41%	1.35	2.18	111	+4.1
4		108	50-32	60.98%	108-73	59.67%	1.32	2.16	108	+2.23
5		107	48-34	58.54%	107-77	58.15%	1.30	2.23	107	+2.48
6		88	44-38	53.66%	88-95	48.09%	1.07	2.00	88	+1.9
7		86	41-41	50.00%	86-98	46.74%	1.05	2.10	86	-0.12
8		75	40-42	48.78%	75-100	42.86%	0.91	1.88	75	-1.13
9		75	39-43	47.56%	75-93	44.64%	0.91	1.92	75	-1.56
10		71	37-45	45.12%	71-104	40.57%	0.87	1.92	71	+0.56
11		52	30-52	36.59%	52-111	31.90%	0.63	1.73	52	-4.29
12		41	24-58	29.27%	41-87	32.03%	0.50	1.71	41	-6.23
13		37	26-56	31.71%	37-93	28.46%	0.45	1.42	37	-7.11
14		25	19-63	23.17%	25-89	21.93%	0.30	1.32	25	-9.11
15		23	18-64	21.95%	23-97	19.17%	0.28	1.28	23	-12.44

WestStandings <- Standings %>%
  filter(!home_abbreviation %in% east) %>%
  select(-home_abbreviation) %>%
  arrange(-Pts, PPW, -AdjWP) %>%
  mutate(Rk = 1:15) %>%
  select(12, 1:11)
gt(WestStandings) %>%
    gt_theme_espn() %>%
    cols_align(columns = everything(), align = c('center')) %>%
    cols_align(columns = c(Rk), align = c('right')) %>%
    text_transform(locations = cells_body(columns = home_logo),
      fn = function(x) {web_image(url = WestStandings$home_logo, height = as.numeric(40))}) %>%
    fmt_percent(columns = c(WP, AdjWP), decimals = 2) %>%
    fmt_number(columns = c(PPG, PPW)) %>%
    gt_highlight_rows(rows = 1:6, fill = "#8CD47E") %>%
    gt_highlight_rows(rows = 7:10, fill = "#F8D66D") %>%
    gt_highlight_rows(rows = 11:15, fill = "#FF6961") %>%
    tab_style(style = list(cell_fill(color = "black"), cell_text(color = "white", align = "center")), locations = cells_column_labels()) %>%
    cols_label(home_logo = "", 
               WL = "W-L",
               WP = "Pct",
               AdjWL = "Adj. W-L",
               AdjWP = "Adj. Pct",
               MPts = "Max Pts") %>%
    cols_width(Rk ~ px(25), home_logo ~ px(67), Pts ~ px(50), WL ~ px(60), WP ~ px(60), AdjWL ~ px(75), AdjWP ~ px(75), PPG ~ px(50), PPW ~ px(50), MPts ~ px(75), PD ~ px(60)) %>%
    tab_header(title = "WESTERN CONFERENCE STANDINGS") %>%
    tab_style(style = list(cell_fill(color = "#c9082A"), cell_text(color = "white", align = "center")), locations = cells_title()) %>%
    cols_hide(Team)

WESTERN CONFERENCE STANDINGS
Rk		Pts	W-L	Pct	Adj. W-L	Adj. Pct	PPG	PPW	Max Pts	PD
1		182	68-14	82.93%	182-73	71.37%	2.22	2.68	182	+12.87
2		114	52-30	63.41%	114-89	56.16%	1.39	2.19	114	+4.51
3		110	50-32	60.98%	110-84	56.70%	1.34	2.20	110	+4.66
4		109	50-32	60.98%	109-88	55.33%	1.33	2.18	109	+1.22
5		107	50-32	60.98%	107-92	53.77%	1.30	2.14	107	+3.89
6		105	49-33	59.76%	105-97	51.98%	1.28	2.14	105	+5
7		105	48-34	58.54%	105-102	50.72%	1.28	2.19	105	+3.3
8		102	48-34	58.54%	102-92	52.58%	1.24	2.12	102	+4.85
9		76	40-42	48.78%	76-94	44.71%	0.93	1.90	76	+0.48
10		76	39-43	47.56%	76-100	43.18%	0.93	1.95	76	-1.2
11		66	36-46	43.90%	66-88	42.86%	0.80	1.83	66	-2.98
12		65	36-46	43.90%	65-95	40.62%	0.79	1.81	65	-3
13		57	34-48	41.46%	57-95	37.50%	0.70	1.68	57	-2.76
14		28	21-61	25.61%	28-103	21.37%	0.34	1.33	28	-9.43
15		20	17-65	20.73%	20-88	18.52%	0.24	1.18	20	-9.34

TotalSchedule <- bind_rows(Schedules)
HomeSchedule <- TotalSchedule %>%
  filter(Game == "Home") %>%
  rename(HLeg = Leg,
         HRunWins = RunWins,
         HPoints = Points,
         HPointsPlaying = PointsPlaying,
         HGameLeg = GameLeg,
         HRunningPts = RunningPts) %>%
  select(game_id, HLeg, HRunWins, HPoints, HPointsPlaying, HGameLeg, HRunningPts)
TotalSchedule <- TotalSchedule %>%
  filter(Game == "Away") %>%
  rename(ALeg = Leg,
         ARunWins = RunWins,
         APoints = Points,
         APointsPlaying = PointsPlaying,
         AGameLeg = GameLeg,
         ARunningPts = RunningPts) %>%
  left_join(HomeSchedule, by = "game_id") %>%
  rename(Away = Team,
         AScore = TeamScore,
         HScore = OpponentScore,
         Home = Opponent,
         AwayWin = TeamWin) %>%
  select(-OpponentLogo,-Opponent2, -Game) %>%
  mutate(date = substr(date, 1, 10),
         date = as.Date(date)) %>%
  group_by(APointsPlaying, HPointsPlaying) %>%
  mutate(Total = n()) %>%
  ungroup() %>%
  mutate(PointsPlaying = APointsPlaying+HPointsPlaying)

ggplot(TotalSchedule) +
  geom_tile(aes(x = APointsPlaying, y = HPointsPlaying), fill = "#1D3557", color = "#3E92CC") +
  geom_text(aes(x = APointsPlaying, y = HPointsPlaying, label = Total), color = "white", size = 9) +
  coord_fixed() +
  theme_McCadeP8() +
  labs(x = "Away Playing For",
       y = "Home Playing For",
       title = "Octopus Points Played For Each Game",
       caption = "@McCadeP8 | Data: nba.com") +
  theme(panel.background = element_blank())

TotalSchedule <- bind_rows(Schedules)
TotalSchedule <- TotalSchedule %>%
  left_join(Teams, by = c('Team' = 'home_name')) %>%
  mutate(date = substr(date, 1, 10),
         date = as.Date(date),
         Conf = ifelse(home_abbreviation %in% east, "Eastern Conference", "Western Conference"),
         home_color = paste0("#",home_color))
BaseTable <- 
  expand.grid(Team = unique(all_schedule$home_name), 
              Date = seq(as.Date("2024-10-22"), as.Date("2025-04-13"), by = "day"),
              Frame = seq(as.Date("2024-11-19"), as.Date("2025-04-13"), by = "day")) %>%
  mutate(Team = as.character(Team),
         DaysDiff = Frame-Date) %>%
  filter(DaysDiff >= 0 & DaysDiff <= 28) %>%
  select(-DaysDiff) %>%
  mutate(Frame = Frame-as.Date("2024-11-18"),
         Frame = as.numeric(Frame)) %>%
  left_join(TotalSchedule, by = c('Team', 'Date' = 'date')) %>%
  mutate(PlayedToday = ifelse(is.na(TeamScore == T), F, T)) %>%
  select(Team, Date, RunningPts, PlayedToday, Frame) %>%
  arrange(Team, Frame, Date)
StandingsByDay <- BaseTable %>%
  select(Team, Date, RunningPts) %>%
  arrange(Team, Date) %>%
  group_by(Team) %>%
  fill(RunningPts, .direction = "down") %>%
  ungroup() %>%
  mutate(RunningPts = ifelse(is.na(RunningPts) == T, 0, RunningPts)) %>%
  left_join(Teams, by = c('Team' = 'home_name')) %>%
  mutate(home_color = paste0("#",home_color),
         home_alternate_color = paste0("#",home_alternate_color),
         Conf = ifelse(home_abbreviation %in% east, "EASTERN CONFERENCE", "WESTERN CONFERENCE")) %>%
  distinct()
BaseTable <- BaseTable %>%
  select(-RunningPts) %>%
  left_join(StandingsByDay, by = c('Team', 'Date'))
LabelData <- BaseTable %>%
  group_by(Team, Frame) %>%
  mutate(Rk = n():1) %>%
  filter(Rk == 1) %>%
  select(-Rk)
Games <- BaseTable %>%
  filter(PlayedToday == T)

ggplot() +
    geom_line(data = BaseTable, aes(x = Date, y = RunningPts, group = Team, color = home_color), size = 1) +
    geom_point(data = Games, aes(x = Date+0.5, y = RunningPts, color = home_color), size = 4) +
    geom_label(data = LabelData, aes(x = Date, y = RunningPts, label = Team, fill = home_color, color = home_alternate_color), hjust = 0) +    
    scale_color_identity() +
    scale_fill_identity() +
    scale_x_date(date_labels = "%b %e", date_breaks = "2 days") +
    scale_y_continuous(position = "right", breaks = seq(0,180, by = 20), labels = function(x) paste0(x, "Pts")) +
    theme_McCadeP8() +
    theme(axis.text = element_text(size = 12), strip.text = element_text(size = 14, face = "bold")) +
    labs(title = "NBA Standings: Octopus Point Format", 
         x = "", 
         y = "") +
    facet_wrap(~Conf, ncol = 1) +
    transition_states(Frame) +
    ease_aes('linear') +
    view_follow(fixed_x = FALSE)

#animate(p, width = 1600, height = 1200, fps = 4, duration = 36, renderer = gifski_renderer("nba_standings_animation.gif"))

TotalSchedule <- bind_rows(Schedules)
HomeSchedule <- TotalSchedule %>%
  filter(Game == "Home") %>%
  rename(HLeg = Leg,
         HRunWins = RunWins,
         HPoints = Points,
         HPointsPlaying = PointsPlaying,
         HGameLeg = GameLeg,
         HRunningPts = RunningPts) %>%
  select(game_id, HLeg, HRunWins, HPoints, HPointsPlaying, HGameLeg, HRunningPts)
TotalSchedule <- TotalSchedule %>%
  filter(Game == "Away") %>%
  rename(
    ALeg = Leg,
    ARunWins = RunWins,
    APoints = Points,
    APointsPlaying = PointsPlaying,
    AGameLeg = GameLeg,
    ARunningPts = RunningPts) %>%
  left_join(HomeSchedule, by = "game_id") %>%
  rename(Away = Team,
         AScore = TeamScore,
         HScore = OpponentScore,
         Home = Opponent,
         AwayWin = TeamWin) %>%
  select(-OpponentLogo,-Opponent2, -Game) %>%
  mutate(date = substr(date, 1, 10),
         date = as.Date(date)) %>%
  group_by(APointsPlaying, HPointsPlaying) %>%
  mutate(Total = n()) %>%
  ungroup() %>%
  mutate(PointsPlaying = APointsPlaying + HPointsPlaying)
DailyAvg <- TotalSchedule %>%
  group_by(date) %>%
  summarise(DailyPts = mean(PointsPlaying), .groups = 'drop') %>%
  arrange(date) %>%
  mutate(RollAvg = rollmean(DailyPts, k = 4, fill = NA, align = "right")) %>%
  select(date, RollAvg)
TotalSchedule <- TotalSchedule %>%
  left_join(DailyAvg, by = "date") %>%
  select(date, PointsPlaying, RollAvg) %>%
  mutate(Day = as.numeric(date)-20017)
TotalSchedule$PointsPlaying <- TotalSchedule$PointsPlaying + 
  runif(nrow(TotalSchedule), min = -0.33, max = 0.33)
Total <- map(1:174, ~ mutate(TotalSchedule, Frame = .x))
TotalSchedule <- bind_rows(Total)
TotalSchedule <- TotalSchedule %>%
  mutate(Test = Day-Frame,
         RollAvg = ifelse(Test > 0, NA, RollAvg)) %>%
  select(date, PointsPlaying, RollAvg, Frame, Day, Test) %>%
  mutate(Frame = Frame-3) %>%
  filter(Frame >= 1) %>%
  arrange(Frame, date)

ggplot(TotalSchedule) +
  geom_point(aes(x = date, y = PointsPlaying), color = "#CCCCCC", alpha = 0.6) +
  scale_y_continuous(breaks = 2:12, labels = 2:12, limits = c(1,12)) +
  labs(title = "Eight Arms of Urgency: Unveiling the OCTOPUS Point System for NBA Games",
       y = "Combined Incentive Score",
       x = NULL,
       caption = "@McCadeP8 | Data: nba.com") +
  theme_McCadeP8() +
  theme(axis.text.x = element_text(angle = 0, hjust = 0.5)) +
  geom_line(aes(x = date, y = RollAvg), color = "#CC0000", size = 1.2) +
  transition_states(Frame,
                   transition_length = 1,
                   state_length = 1)

#animate(p, duration = 8, fps = 10, width = 1000, height = 616, start_pause = 5, end_pause = 10, renderer = gifski_renderer("game_value.gif"))

team_dfs <- list()

for (team_name in names(Schedules)) {
  
  df <- Schedules[[team_name]]
  
  leg_summary <- df %>%
    group_by(Team, Leg) %>%
    summarise(
      TeamWins = list(TeamWin),
      TotalWins = sum(TeamWin),
      TotalPoints = sum(Points),
      .groups = "drop"
    )
  
  leg_summary_wide <- leg_summary %>%
    mutate(Leg = paste0("Leg", Leg)) %>%
    pivot_wider(
      names_from = Leg,
      values_from = c(TeamWins, TotalWins, TotalPoints),
      names_glue = "{.value}_{Leg}"
    )
  
  leg_cols_ordered <- c("Team", unlist(map(1:8, function(i) {
    paste0(c("TeamWins_Leg", "TotalWins_Leg", "TotalPoints_Leg"), i)
  })))
  
  team_df <- leg_summary_wide %>%
    select(all_of(leg_cols_ordered)) %>%
    mutate(
      TotalWins = TotalWins_Leg1 + TotalWins_Leg2 + TotalWins_Leg3 + TotalWins_Leg4 +
                  TotalWins_Leg5 + TotalWins_Leg6 + TotalWins_Leg7 + TotalWins_Leg8,
      TotalPoints = TotalPoints_Leg1 + TotalPoints_Leg2 + TotalPoints_Leg3 + TotalPoints_Leg4 +
                    TotalPoints_Leg5 + TotalPoints_Leg6 + TotalPoints_Leg7 + TotalPoints_Leg8,
      TotalWins_Leg1 = paste0(TotalWins_Leg1, "-", 10 - TotalWins_Leg1),
      TotalPoints_Leg1 = paste0(TotalPoints_Leg1, "pts"),
      TotalWins_Leg2 = paste0(TotalWins_Leg2, "-", 10 - TotalWins_Leg2),
      TotalPoints_Leg2 = paste0(TotalPoints_Leg2, "pts"),
      TotalWins_Leg3 = paste0(TotalWins_Leg3, "-", 10 - TotalWins_Leg3),
      TotalPoints_Leg3 = paste0(TotalPoints_Leg3, "pts"),
      TotalWins_Leg4 = paste0(TotalWins_Leg4, "-", 10 - TotalWins_Leg4),
      TotalPoints_Leg4 = paste0(TotalPoints_Leg4, "pts"),
      TotalWins_Leg5 = paste0(TotalWins_Leg5, "-", 10 - TotalWins_Leg5),
      TotalPoints_Leg5 = paste0(TotalPoints_Leg5, "pts"),
      TotalWins_Leg6 = paste0(TotalWins_Leg6, "-", 10 - TotalWins_Leg6),
      TotalPoints_Leg6 = paste0(TotalPoints_Leg6, "pts"),
      TotalWins_Leg7 = paste0(TotalWins_Leg7, "-", 10 - TotalWins_Leg7),
      TotalPoints_Leg7 = paste0(TotalPoints_Leg7, "pts"),
      TotalWins_Leg8 = paste0(TotalWins_Leg8, "-", 12 - TotalWins_Leg8),
      TotalPoints_Leg8 = paste0(TotalPoints_Leg8, "pts"),
      TotalWins = paste0(TotalWins, "-", 82 - TotalWins))
  team_dfs[[team_name]] <- team_df}

FinalDF <- bind_rows(team_dfs)

FinalDF <- FinalDF %>%
  arrange(-TotalPoints) %>%
  mutate(TotalPoints = paste0(TotalPoints,"pts")) %>%
  left_join(Teams, by = c('Team' = 'home_name')) %>%
  select(-Team, -home_alternate_color, -home_display_name, -home_color, -home_abbreviation) %>%
  select(27, 1:26)

gt(FinalDF) %>%
  gt_theme_espn() %>%
  text_transform(locations = cells_body(columns = home_logo),
    fn = function(x) {web_image(url = FinalDF$home_logo, height = as.numeric(40))}) %>%
  gt_plt_winloss(TeamWins_Leg1, type = "pill", max_wins = 10, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg1, col2 = TotalPoints_Leg1) %>%
  gt_plt_winloss(TeamWins_Leg2, type = "pill", max_wins = 10, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg2, col2 = TotalPoints_Leg2) %>%
  gt_plt_winloss(TeamWins_Leg3, type = "pill", max_wins = 10, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg3, col2 = TotalPoints_Leg3) %>%
  gt_plt_winloss(TeamWins_Leg4, type = "pill", max_wins = 10, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg4, col2 = TotalPoints_Leg4) %>%
  gt_plt_winloss(TeamWins_Leg5, type = "pill", max_wins = 10, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg5, col2 = TotalPoints_Leg5) %>%
  gt_plt_winloss(TeamWins_Leg6, type = "pill", max_wins = 10, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg6, col2 = TotalPoints_Leg6) %>%
  gt_plt_winloss(TeamWins_Leg7, type = "pill", max_wins = 10, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg7, col2 = TotalPoints_Leg7) %>%
  gt_plt_winloss(TeamWins_Leg8, type = "pill", max_wins = 12, palette = c("#8CD47E", "#FF6961", "gray")) %>%
  gt_merge_stack(col1 = TotalWins_Leg8, col2 = TotalPoints_Leg8) %>%
  cols_label(TeamWins_Leg1 = "Game Log", 
             TotalWins_Leg1 = "Record",
             TeamWins_Leg2 = "Game Log", 
             TotalWins_Leg2 = "Record",
             TeamWins_Leg3 = "Game Log", 
             TotalWins_Leg3 = "Record",
             TeamWins_Leg4 = "Game Log", 
             TotalWins_Leg4 = "Record",
             TeamWins_Leg5 = "Game Log", 
             TotalWins_Leg5 = "Record",
             TeamWins_Leg6 = "Game Log", 
             TotalWins_Leg6 = "Record",
             TeamWins_Leg7 = "Game Log", 
             TotalWins_Leg7 = "Record",
             TeamWins_Leg8 = "Game Log", 
             TotalWins_Leg8 = "Record",
             TotalWins = "Record", 
             TotalPoints = "Points",
             home_logo = "") %>%
  tab_spanner(label = "Leg 1", columns = c(TeamWins_Leg1, TotalWins_Leg1)) %>%
  tab_spanner(label = "Leg 2", columns = c(TeamWins_Leg2, TotalWins_Leg2)) %>%
  tab_spanner(label = "Leg 3", columns = c(TeamWins_Leg3, TotalWins_Leg3)) %>%
  tab_spanner(label = "Leg 4", columns = c(TeamWins_Leg4, TotalWins_Leg4)) %>%
  tab_spanner(label = "Leg 5", columns = c(TeamWins_Leg5, TotalWins_Leg5)) %>%
  tab_spanner(label = "Leg 6", columns = c(TeamWins_Leg6, TotalWins_Leg6)) %>%
  tab_spanner(label = "Leg 7", columns = c(TeamWins_Leg7, TotalWins_Leg7)) %>%
  tab_spanner(label = "Leg 8", columns = c(TeamWins_Leg8, TotalWins_Leg8)) %>%
  tab_spanner(label = "Total", columns = c(TotalWins, TotalPoints)) %>%
  cols_align(columns = everything(), align = c('center')) %>%
  tab_source_note(source_note = "@McCadeP8 | Data: nba.com") %>%
  tab_header(title = md("**Big Picture View of Octopus Format in 2024-25 Season**")) %>%
  opt_align_table_header(align = c('center'))

Big Picture View of Octopus Format in 2024-25 Season
	Leg 1		Leg 2		Leg 3		Leg 4		Leg 5		Leg 6		Leg 7		Leg 8		Total
	Game Log	Record	Game Log	Record	Game Log	Record	Game Log	Record	Game Log	Record	Game Log	Record	Game Log	Record	Game Log	Record	Record	Points
		8-2 20pts		7-3 16pts		10-0 30pts		9-1 25pts		7-3 16pts		8-2 20pts		9-1 25pts		10-2 30pts	68-14	182pts
		10-0 30pts		7-3 16pts		9-1 25pts		8-2 20pts		6-4 12pts		10-0 30pts		6-4 12pts		8-4 20pts	64-18	165pts
		8-2 20pts		8-2 20pts		6-4 12pts		6-4 12pts		7-3 16pts		7-3 16pts		9-1 25pts		10-2 30pts	61-21	151pts
		6-4 12pts		8-2 20pts		7-3 16pts		6-4 12pts		5-5 9pts		5-5 9pts		8-2 20pts		7-5 16pts	52-30	114pts
		5-5 9pts		7-3 16pts		8-2 20pts		6-4 12pts		7-3 16pts		7-3 16pts		4-6 6pts		7-5 16pts	51-31	111pts
		6-4 12pts		6-4 12pts		5-5 9pts		6-4 12pts		5-5 9pts		4-6 6pts		8-2 20pts		10-2 30pts	50-32	110pts
		6-4 12pts		6-4 12pts		5-5 9pts		5-5 9pts		9-1 25pts		8-2 20pts		4-6 6pts		7-5 16pts	50-32	109pts
		5-5 9pts		4-6 6pts		6-4 12pts		7-3 16pts		7-3 16pts		6-4 12pts		6-4 12pts		9-3 25pts	50-32	108pts
		2-8 2pts		9-1 25pts		5-5 9pts		7-3 16pts		4-6 6pts		8-2 20pts		5-5 9pts		8-4 20pts	48-34	107pts
		7-3 16pts		4-6 6pts		6-4 12pts		7-3 16pts		7-3 16pts		8-2 20pts		5-5 9pts		6-6 12pts	50-32	107pts
		6-4 12pts		4-6 6pts		6-4 12pts		5-5 9pts		6-4 12pts		5-5 9pts		8-2 20pts		9-3 25pts	49-33	105pts
		8-2 20pts		4-6 6pts		3-7 4pts		5-5 9pts		5-5 9pts		7-3 16pts		9-1 25pts		7-5 16pts	48-34	105pts
		6-4 12pts		7-3 16pts		7-3 16pts		5-5 9pts		9-1 25pts		4-6 6pts		5-5 9pts		5-7 9pts	48-34	102pts
		4-6 6pts		4-6 6pts		5-5 9pts		8-2 20pts		4-6 6pts		8-2 20pts		6-4 12pts		5-7 9pts	44-38	88pts
		4-6 6pts		9-1 25pts		5-5 9pts		4-6 6pts		2-8 2pts		5-5 9pts		3-7 4pts		9-3 25pts	41-41	86pts
		6-4 12pts		3-7 4pts		4-6 6pts		7-3 16pts		5-5 9pts		7-3 16pts		3-7 4pts		5-7 9pts	40-42	76pts
		5-5 9pts		7-3 16pts		7-3 16pts		3-7 4pts		4-6 6pts		6-4 12pts		1-9 1pts		6-6 12pts	39-43	76pts
		4-6 6pts		5-5 9pts		6-4 12pts		6-4 12pts		2-8 2pts		4-6 6pts		7-3 16pts		6-6 12pts	40-42	75pts
		4-6 6pts		4-6 6pts		5-5 9pts		5-5 9pts		3-7 4pts		3-7 4pts		6-4 12pts		9-3 25pts	39-43	75pts
		4-6 6pts		6-4 12pts		6-4 12pts		4-6 6pts		5-5 9pts		4-6 6pts		0-10 0pts		8-4 20pts	37-45	71pts
		3-7 4pts		5-5 9pts		2-8 2pts		3-7 4pts		8-2 20pts		6-4 12pts		4-6 6pts		5-7 9pts	36-46	66pts
		8-2 20pts		4-6 6pts		3-7 4pts		5-5 9pts		5-5 9pts		3-7 4pts		5-5 9pts		3-9 4pts	36-46	65pts
		4-6 6pts		7-3 16pts		4-6 6pts		4-6 6pts		3-7 4pts		4-6 6pts		5-5 9pts		3-9 4pts	34-48	57pts
		2-8 2pts		3-7 4pts		2-8 2pts		2-8 2pts		7-3 16pts		2-8 2pts		6-4 12pts		6-6 12pts	30-52	52pts
		2-8 2pts		3-7 4pts		8-2 20pts		2-8 2pts		5-5 9pts		1-9 1pts		2-8 2pts		1-11 1pts	24-58	41pts
		4-6 6pts		5-5 9pts		3-7 4pts		2-8 2pts		3-7 4pts		4-6 6pts		2-8 2pts		3-9 4pts	26-56	37pts
		3-7 4pts		1-9 1pts		1-9 1pts		3-7 4pts		4-6 6pts		4-6 6pts		3-7 4pts		2-10 2pts	21-61	28pts
		4-6 6pts		2-8 2pts		1-9 1pts		4-6 6pts		2-8 2pts		1-9 1pts		4-6 6pts		1-11 1pts	19-63	25pts
		2-8 2pts		0-10 0pts		3-7 4pts		1-9 1pts		3-7 4pts		2-8 2pts		4-6 6pts		3-9 4pts	18-64	23pts
		2-8 2pts		2-8 2pts		3-7 4pts		3-7 4pts		2-8 2pts		3-7 4pts		1-9 1pts		1-11 1pts	17-65	20pts
@McCadeP8 | Data: nba.com

TotalSchedule <- bind_rows(Schedules)
TotalResults <- TotalSchedule %>%
  mutate(Leg2 = paste("Leg", Leg)) %>%
  group_by(Team, Leg, Leg2) %>%
  summarize(Total = sum(Points),
            Total2 = sum(TeamWin)) %>%
  left_join(Teams, by = c('Team' = 'home_name')) %>%
  mutate(home_color = paste0("#",home_color),
         home_alternate_color = paste0("#",home_alternate_color)) %>%
  arrange(home_display_name)

ggplot(TotalResults) +
  geom_col(aes(x = as.character(Leg), y = Total2), width = 1, fill = TotalResults$home_color, color = TotalResults$home_alternate_color) +
  coord_polar() +
  scale_y_continuous(breaks = 0:12, labels = c(0, 1, 2, 4, 6, 9, 12, 16, 20, 25, 30, 36, 42), limits = c(0, 12)) +
  scale_x_discrete(breaks = 1:8, labels = 1:8) +
  theme_McCadeP8() +
  theme(axis.text.x = element_text(face = "bold")) +
  facet_wrap(~home_display_name, ncol = 6) +
  theme_McCadeP8() +
  theme(axis.text.x = element_text(face = "bold"),
        axis.text.y = element_text(face = "bold", size = 9),
        strip.text = element_text(face = "bold", color = "white", size = 13),
        strip.background = element_rect(fill = "#326DA8"),
        plot.title = element_text(face = "bold", size = 30, hjust = 0.5),
        plot.caption = element_text(size = 14)) +
  labs(x = NULL,
       y = "Octopus Points",
       title = "Who Has Success Throughout the Season by Leg (Octopus Format)",
       caption = "@McCadeP8 | Data: nba.com")

TotalSchedule <- bind_rows(Schedules)
TotalSchedule <- TotalSchedule %>%
  mutate(date = as.Date(date))

ListOfDates <- seq(as.Date("2024-10-22"), as.Date("2025-04-13"), by = "day")
ResultsByDate <- vector("list", length(ListOfDates))
for (i in seq_along(ListOfDates)) {
  CurrentDay <- ListOfDates[i]
  DateCheck <- TotalSchedule %>%
    select(date, Team, TeamWin, Leg) %>%
    group_by(Team, Leg) %>%
    mutate(CurrentDate = CurrentDay,
           TeamWin = ifelse(date <= CurrentDay, TeamWin, 1),
           RunWins = cumsum(TeamWin),
           Points = ifelse(TeamWin == 1, getPoints(RunWins), 0),
           PointsPlaying = getPoints(RunWins),
           PointsPlaying = ifelse(PointsPlaying == 0, 1, PointsPlaying),
           GameLeg = 1:n(),
           Before = ifelse(date <= CurrentDay,T,F)) %>%
    ungroup() %>%
    group_by(Team, Before) %>%
    mutate(WinsToDate = sum(TeamWin),
           PointsToDate = sum(Points)) %>%
    ungroup() %>%
    group_by(Team) %>%
    mutate(MaxWins = sum(TeamWin),
           MaxPoints = sum(Points)) %>%
    filter(Before == TRUE) %>%
    select(Team, CurrentDate, WinsToDate, PointsToDate, MaxWins, MaxPoints) %>%
    distinct()
  ResultsByDate[[i]] <- DateCheck}
FinalResults <- bind_rows(ResultsByDate)
FinalResults <- FinalResults %>%
  left_join(Teams, by = c('Team' = 'home_name')) %>%
  mutate(home_color = paste0("#",home_color),
         home_alternate_color = paste0("#",home_alternate_color),
         Conf = ifelse(home_abbreviation %in% east, "East", "West"))
Wins6 <- FinalResults %>%
  group_by(CurrentDate, Conf) %>%
  mutate(WinsRank = rank(-WinsToDate, ties.method = "random"),
         Place6Wins = WinsToDate) %>%
  filter(WinsRank == 6) %>%
  select(CurrentDate, Conf, Place6Wins)
Wins10 <- FinalResults %>%
  group_by(CurrentDate, Conf) %>%
  mutate(WinsRank = rank(-WinsToDate, ties.method = "random"),
         Place10Wins = WinsToDate) %>%
  filter(WinsRank == 10) %>%
  select(CurrentDate, Conf, Place10Wins)
Pts6 <- FinalResults %>%
  group_by(CurrentDate, Conf) %>%
  mutate(PtsRank = rank(-PointsToDate, ties.method = "random"),
         Place6Pts = PointsToDate) %>%
  filter(PtsRank == 6) %>%
  select(CurrentDate, Conf, Place6Pts)
Pts10 <- FinalResults %>%
  group_by(CurrentDate, Conf) %>%
  mutate(PtsRank = rank(-PointsToDate, ties.method = "random"),
         Place10Pts = PointsToDate) %>%
  filter(PtsRank == 10) %>%
  select(CurrentDate, Conf, Place10Pts)
FinalResultsV2 <- FinalResults %>%
  ungroup() %>%
  left_join(Wins6, by = c('CurrentDate','Conf')) %>%
  left_join(Wins10, by = c('CurrentDate','Conf')) %>%
  left_join(Pts6, by = c('CurrentDate','Conf')) %>%
  left_join(Pts10, by = c('CurrentDate','Conf')) %>%
  mutate(Alive6Win = ifelse(MaxWins >= Place6Wins, "Yes", "No"),
         Alive10Win = ifelse(MaxWins >= Place10Wins, "Yes", "No"),
         Alive6Pts = ifelse(MaxPoints >= Place6Pts, "Yes", "No"),
         Alive6Pts = ifelse(Team == "Warriors" & CurrentDate == as.Date('2025-04-13'), "No", Alive6Pts),
         Alive10Pts = ifelse(MaxPoints >= Place10Pts, "Yes", "No")) %>%
  arrange(CurrentDate)
Wins6Eligible <- FinalResultsV2 %>%
  group_by(Team, Alive6Win) %>%
  mutate(LastDay = 1:n()) %>%
  filter(Alive6Win == "No" & LastDay == 1) %>%
  mutate(Type = "EligibleWins_Playoff Elimination") %>%
  ungroup() %>%
  select(Team, CurrentDate, home_color, home_alternate_color, home_logo, Conf, Type)
Wins10Eligible <- FinalResultsV2 %>%
  group_by(Team, Alive10Win) %>%
  mutate(LastDay = 1:n()) %>%
  filter(Alive10Win == "No" & LastDay == 1) %>%
  mutate(Type = "EligibleWins_Play-In Elimination") %>%
  ungroup() %>%
  select(Team, CurrentDate, home_color, home_alternate_color, home_logo, Conf, Type)
Pts6Eligible <- FinalResultsV2 %>%
  group_by(Team, Alive6Pts) %>%
  mutate(LastDay = 1:n()) %>%
  filter(Alive6Pts == "No" & LastDay == 1) %>%
  mutate(Type = "EligiblePts_Playoff Elimination") %>%
  ungroup() %>%
  select(Team, CurrentDate, home_color, home_alternate_color, home_logo, Conf, Type)
Pts10Eligible <- FinalResultsV2 %>%
  group_by(Team, Alive10Pts) %>%
  mutate(LastDay = 1:n()) %>%
  filter(Alive10Pts == "No" & LastDay == 1) %>%
  mutate(Type = "EligiblePts_Play-In Elimination") %>%
  ungroup() %>%
  select(Team, CurrentDate, home_color, home_alternate_color, home_logo, Conf, Type)
TotalResults3 <- rbind(Wins6Eligible, Wins10Eligible, Pts6Eligible, Pts10Eligible)
TotalResults3 <- TotalResults3 %>%
  separate(Type, into = c("Type", "Size"), sep = "_") %>%
  pivot_wider(names_from = Type, values_from = CurrentDate) %>%
  mutate(Size = fct_rev(factor(Size))) %>%
  group_by(Size) %>%
  mutate(Team = fct_reorder(Team, desc(EligibleWins))) %>%
  ungroup()

ggplot(TotalResults3) +
  geom_segment(aes(x = EligiblePts, xend = EligibleWins, y = Team, yend = Team), color = "white", size = 1) +
  geom_point(aes(x = EligiblePts, y = Team), color = "#C3DDFD", size = 7) +
  geom_point(aes(x = EligibleWins, y = Team), color = "#1D3557", size = 5) +
  facet_wrap(~Size, ncol = 1, scales = "free_y") +
  scale_x_date(breaks = as.Date(c("2025-03-02", "2025-03-09", "2025-03-16", "2025-03-23", "2025-03-30", "2025-04-06", "2025-04-13")), minor_breaks = seq(as.Date("2025-03-01"), as.Date("2025-04-18"), by = "1 day"), labels = date_format("%b %d"), expand = expansion(mult = c(0.05, 0.08))) +
  theme_McCadeP8() +
  theme(axis.text.x = element_text(angle = 45, hjust = 1),
        axis.text.y = element_text(size = 18),
        panel.grid.minor.x = element_line(color = "#333333", linewidth = 0.15),
        panel.grid.major.x = element_line(color = "#666666", linewidth = 0.3),
        strip.text = element_text(face = "bold", color = "white", size = 18),
        strip.background = element_rect(fill = "#326DA8"),
        plot.title = element_markdown(face = "bold", size = 48, hjust = 0.5),
        plot.caption = element_text(size = 18)) +
  labs(x = "", 
       y = "", 
       caption = "@McCadeP8 | Data: nba.com",
       title = "Team Elimination Dates: <span style='color:#1D3557'>Actual</span> vs <span style='color:#C3DDFD'>Octopus</span> Format")

TotalSchedule <- bind_rows(Schedules)
HomeSchedule <- TotalSchedule %>%
  filter(Game == "Home") %>%
  rename(
    HLeg = Leg,
    HRunWins = RunWins,
    HPoints = Points,
    HPointsPlaying = PointsPlaying,
    HGameLeg = GameLeg,
    HRunningPts = RunningPts) %>%
  select(game_id, HLeg, HRunWins, HPoints, HPointsPlaying, HGameLeg, HRunningPts)
TotalSchedule <- TotalSchedule %>%
  filter(Game == "Away") %>%
  rename(
    ALeg = Leg,
    ARunWins = RunWins,
    APoints = Points,
    APointsPlaying = PointsPlaying,
    AGameLeg = GameLeg,
    ARunningPts = RunningPts) %>%
  left_join(HomeSchedule, by = "game_id") %>%
  rename(Away = Team,
         AScore = TeamScore,
         HScore = OpponentScore,
         Home = Opponent,
         AwayWin = TeamWin) %>%
  select(-OpponentLogo,-Opponent2, -Game) %>%
  mutate(date = substr(date, 1, 10),
         date = as.Date(date)) %>%
  group_by(APointsPlaying, HPointsPlaying) %>%
  mutate(Total = n()) %>%
  ungroup() %>%
  mutate(PointsPlaying = APointsPlaying + HPointsPlaying) %>%
  arrange(date) %>%
  filter(APointsPlaying >= 4 & HPointsPlaying >= 4) %>%
  mutate(HRunWins = ifelse(AwayWin == 1, HRunWins, HRunWins-1),
         ARunWins = ifelse(AwayWin == 1, ARunWins-1, ARunWins),
         ARecord = paste0(ARunWins,"-",AGameLeg-1-ARunWins),
         HRecord = paste0(HRunWins,"-",HGameLeg-1-HRunWins),
         APointsPlaying = paste0(APointsPlaying,"pts"),
         HPointsPlaying = paste0(HPointsPlaying,"pts"),
         date = format(date, "%b %e")) %>%
  left_join(Teams, by = c('Away' = 'home_name')) %>%
  left_join(Teams, by = c('Home' = 'home_name')) %>%
  select(HLeg, date, home_logo.x, ARecord, AScore, HScore, HRecord, home_logo.y, APointsPlaying, HPointsPlaying) %>%
  mutate(win_away = ifelse(AScore > HScore, T,F))

gt(TotalSchedule) %>%
  gt_theme_espn() %>%
  text_transform(locations = cells_body(columns = home_logo.x),
      fn = function(x) {web_image(url = TotalSchedule$home_logo.x, height = as.numeric(40))}) %>%
    text_transform(locations = cells_body(columns = home_logo.y),
      fn = function(x) {web_image(url = TotalSchedule$home_logo.y, height = as.numeric(40))}) %>%
  gt_merge_stack(col1 = ARecord, col2 = APointsPlaying) %>%
  gt_merge_stack(col1 = HRecord, col2 = HPointsPlaying) %>%
  cols_align(align = c('center')) %>%
  cols_label(HLeg = "Leg",
             home_logo.x = "Away",
             ARecord = "Leg Record",
             AScore = "Score",
             HScore = "Score",
             HRecord = "Leg Record",
             home_logo.y = "Home") %>%
  tab_header(title = md("**Top Games of the 2024-25 Season**")) %>%
  opt_align_table_header(align = c('center')) %>%
  tab_style(style = cell_fill(color = "#8CD47E"), locations = cells_body(columns = AScore, rows = AScore > HScore)) %>%
  tab_style(style = cell_fill(color = "#8CD47E"), locations = cells_body(columns = HScore, rows = HScore > AScore)) %>%
  tab_style(style = cell_fill(color = "#FF6961"), locations = cells_body(columns = AScore, rows = HScore > AScore)) %>%
  tab_style(style = cell_fill(color = "#FF6961"), locations = cells_body(columns = HScore, rows = AScore > HScore)) %>%
  cols_hide(win_away) %>%
  tab_source_note(source_note = "@McCadeP8 | Data: nba.com")

Top Games of the 2024-25 Season
Leg	date	Away	Leg Record	Score	Score	Leg Record	Home
1	Nov 6		6-1 4pts	118	112	7-1 4pts
1	Nov 8		7-1 4pts	117	136	9-0 5pts
1	Nov 10		7-2 4pts	127	116	8-1 5pts
4	Jan 12		6-3 4pts	108	93	7-0 4pts
4	Jan 16		8-1 5pts	114	134	8-1 5pts
6	Feb 26		7-1 4pts	97	117	7-1 4pts
6	Feb 28		8-0 5pts	123	116	7-2 4pts
6	Feb 28		7-2 4pts	134	119	8-1 5pts
7	Mar 18		6-1 4pts	119	132	6-2 4pts
7	Mar 20		6-3 4pts	114	117	8-1 5pts
8	Apr 8		7-1 4pts	119	117	6-2 4pts
8	Apr 8		6-2 4pts	113	135	6-2 4pts
8	Apr 9		7-2 4pts	117	134	7-2 4pts
8	Apr 9		8-1 5pts	76	96	7-2 4pts
8	Apr 9		7-2 4pts	111	119	6-3 4pts
8	Apr 10		7-2 4pts	112	114	7-2 4pts
8	Apr 11		7-3 4pts	109	140	6-4 4pts
8	Apr 11		7-3 4pts	108	102	6-4 4pts
8	Apr 11		8-2 5pts	129	115	8-2 5pts
8	Apr 13		8-3 5pts	126	118	8-3 5pts
8	Apr 13		9-2 5pts	124	119	7-4 4pts
@McCadeP8 | Data: nba.com